Method, device and pilot tone equipment for acquiring target motion signal

Abstract

This disclosure provides a method, apparatus, and pilot tone device for acquiring target physiological motion signals. The method includes: acquiring multi-channel complex signals received from multiple channels; and obtaining at least one target motion complex signal with interference removed from the multi-channel complex signals using a motion signal synthesis vector corresponding to at least one target motion signal. Specifically, acquiring data received from multiple channels within a set time period includes data without external interference within a first set sub-time period and data with external interference within a second set sub-time period; obtaining an external interference suppression matrix based on this data, and obtaining data with suppressed external interference based on the data without external interference or the data with external interference and the external interference suppression matrix; obtaining a motion signal correlation matrix of at least one target motion signal in the frequency domain based on the frequency range of at least one target motion signal; and using an eigenvector obtained from the eigenvalues ​​of the motion signal correlation matrix as a motion signal synthesis vector.

Description

Technical Field

[0001] This disclosure relates to the field of magnetic resonance technology, and in particular to a method, apparatus, pilot tone device, non-transient computer-readable storage medium storing a computer program, and computer program product for acquiring motion signals of at least one target. Background Technology

[0002] Magnetic resonance imaging (MRI) is a technique that uses the magnetic resonance phenomenon for imaging. The principle of MRI mainly involves the following: Atomic nuclei containing an odd number of protons, such as the hydrogen nuclei widely found in the human body, have protons that have spin motion, acting like tiny magnets. The spin axes of these tiny magnets are not fixed. If an external magnetic field is applied, these tiny magnets will rearrange themselves according to the magnetic field lines, specifically in two directions parallel or antiparallel to the magnetic field lines. The direction parallel to the magnetic field lines is called the positive longitudinal axis, and the direction antiparallel is called the negative longitudinal axis. The atomic nucleus only has a longitudinal magnetization component, which has both direction and amplitude. Exciting the atomic nuclei in an external magnetic field with a radio frequency (RF) pulse of a specific frequency causes their spin axes to deviate from the positive or negative longitudinal axis, producing resonance—this is the magnetic resonance phenomenon. After the spin axes of the excited atomic nuclei deviate from the positive or negative longitudinal axis, the atomic nuclei acquire a transverse magnetization component.

[0003] After the radio frequency pulse is stopped, the excited atomic nuclei emit echo signals, gradually releasing the absorbed energy in the form of electromagnetic waves. Their phase and energy levels are restored to the state before excitation. The echo signals emitted by the atomic nuclei can be further processed through spatial coding and other methods to reconstruct the image.

[0004] Depending on the radiofrequency pulse sequence used, also known as the sequence, image acquisition in magnetic resonance imaging (MRI) takes from milliseconds to seconds. Generally, the longer the acquisition time, the less noise artifacts. Therefore, it is meaningful to begin image acquisition at the start of a phase where the body is relatively still to avoid motion artifacts caused by movement during image acquisition. However, there are unavoidable movements, such as breathing and heartbeat. Here, a relatively still phase follows the phase of movement, such as after exhalation or myocardial contraction. Image acquisition during this phase has a relatively long duration and is expected to involve less movement, thus allowing for the prediction of the best measurement results. Summary of the Invention

[0005] According to one aspect of this disclosure, a method for acquiring a target motion signal is proposed, comprising: acquiring a multi-channel complex signal received by multiple channels, each of the multi-channel complex signals being a signal received after a high-frequency signal in magnetic resonance scanning is modulated by at least one target motion signal of the scanned object; and obtaining at least one target motion complex signal with interference removed from the multi-channel complex signal using a motion signal synthesis vector corresponding to at least one target motion signal. The motion signal synthesis vector corresponding to at least one target motion signal is obtained by: acquiring data received by multiple channels within a set time period, wherein the data received by multiple channels within the set time period includes data without external interference in a first set sub-time period and data with external interference in a second set sub-time period; obtaining an external interference suppression matrix based on the data without external interference in the first set sub-time period and the data with external interference in the second set sub-time period, and obtaining data with suppressed external interference based on the data without external interference or the data with external interference and the external interference suppression matrix; obtaining a motion signal correlation matrix of at least one target motion signal in the frequency domain based on the data with suppressed external interference and the frequency range of at least one target motion signal; and using an eigenvector obtained from the eigenvalues ​​of the motion signal correlation matrix as the motion signal synthesis vector.

[0006] According to another aspect of this disclosure, an apparatus for acquiring at least one target motion signal is provided, the apparatus comprising: a first unit configured to acquire a multi-channel complex signal received by a plurality of channels, each of the multi-channel complex signals being a signal received after a high-frequency signal in a magnetic resonance scan is modulated by at least one target motion signal of the scanned object; and a second unit configured to obtain, by means of a motion signal synthesis vector corresponding to at least one target motion signal, an interference-free target motion complex signal from the multi-channel complex signal. The second unit includes: a first subunit configured to acquire data received by multiple channels within a set time period, wherein the data received by multiple channels within the set time period includes data without external interference within a first set sub-time period and data with external interference within a second set sub-time period; a second subunit configured to obtain an external interference suppression matrix based on the data without external interference within the first set sub-time period and the data with external interference within the second set sub-time period for each of the at least one time period, and to obtain data with suppressed external interference based on the data without external interference or the data with external interference and the external interference suppression matrix; a third subunit configured to obtain a motion signal correlation matrix of at least one target motion signal in the frequency domain based on the data with suppressed external interference and the frequency of at least one target motion signal; and a fourth subunit configured to use the eigenvector obtained according to the eigenvalues ​​of the motion signal correlation matrix as the motion signal synthesis vector.

[0007] According to another aspect of this disclosure, a pilot tone device is proposed, comprising: a transmitter for transmitting a high-frequency signal, the high-frequency signal being a radio frequency signal outside the frequency band of a magnetic resonance radio frequency signal; a multi-channel receiver for receiving a high-frequency signal modulated by a first target motion signal and a second target motion signal of a scanned object during a magnetic resonance scan; and an electronic device. The electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program that, when executed by the at least one processor, implements the method described above.

[0008] According to another aspect of this disclosure, a non-transitory computer-readable storage medium storing a computer program is provided, wherein the computer program implements the methods described above when executed by a processor.

[0009] According to another aspect of this disclosure, a computer program product is proposed, comprising a computer program that, when executed by a processor, implements the methods described above. Attached Figure Description

[0010] The embodiments of this disclosure will now be described in detail with reference to the accompanying drawings, which will make the above and other features and advantages of the invention more apparent to those skilled in the art. In the drawings:

[0011] Figure 1 A flowchart is shown showing a method for obtaining the motion of at least one target according to some embodiments of the present disclosure;

[0012] Figure 2 A flowchart is shown illustrating a method for obtaining at least one target motion signal corresponding to at least one target motion signal in a method for obtaining at least one target motion according to some embodiments of the present disclosure;

[0013] Figure 3 A flowchart for obtaining an external interference suppression matrix is ​​shown in a method for obtaining the motion of at least one target according to some embodiments of the present disclosure;

[0014] Figure 4 A schematic pilot tone signal received by one channel is shown;

[0015] Figure 5 A flowchart illustrating the process of obtaining at least one target motion correlation matrix in a method for obtaining at least one target motion according to some embodiments of the present disclosure is shown;

[0016] Figure 6 A flowchart illustrating the process of obtaining a first target motion correlation matrix and a second target motion correlation matrix in a method for obtaining the motion of at least one target according to some embodiments of the present disclosure is shown.

[0017] Figure 7A and Figure 7B The signals before and after rotation according to some embodiments of the present disclosure are shown respectively; and

[0018] Figure 8 A block diagram of an apparatus for acquiring the motion of at least one target according to some embodiments of the present disclosure is shown. Detailed Implementation

[0019] To provide a clearer understanding of the technical features, objectives, and effects of this disclosure, specific embodiments of this disclosure will now be described with reference to the accompanying drawings, in which the same reference numerals denote the same parts.

[0020] In this document, “illustrative” means “serving as an example, illustration or description”, and any illustration or implementation described herein as “illustrative” should not be construed as a more preferred or advantageous technical solution.

[0021] To keep the drawings concise, each drawing only schematically shows the parts relevant to this disclosure, and they do not represent the actual structure of the product. Furthermore, to facilitate understanding, in some drawings, components with the same structure or function are shown only schematically, or only one is labeled.

[0022] In this article, "one" can mean not only "only one" but also "more than one". In this article, "first", "second", etc., are used only to distinguish one from another, not to indicate their importance, order, or mutual dependence.

[0023] In magnetic resonance imaging (MRI), to obtain clear clinical diagnostic images, the subject must remain stationary during the scan, especially for certain motion-sensitive sequences. However, some motion of the subject is unavoidable, such as physiological movements caused by respiration and heartbeat. To minimize the impact of motion, various methods are employed to detect these movements, such as breathing bands, electrocardiogram (ECG) gating, and prospective acquisition correction (PACE). By capturing these movements, MRI sequences and signal acquisition can be triggered or gated during periods of minimal motion, such as the plateau phase of a patient's inspiration or expiration. These methods require additional and complex operations. Furthermore, they necessitate the placement of additional sensors on the subject, resulting in a poor user experience.

[0024] Another method for detecting the aforementioned motion is to utilize a pilot tone device that can be integrated into a local coil. The pilot tone device includes a transmitting antenna that transmits a high-frequency signal, such as a radio frequency signal outside the MRI band. This high-frequency signal interacts with the scanned object through attenuation, reflection, and / or interference, and is then received by the local coil to obtain a pilot tone signal. The amplitude / phase of the received pilot tone signal changes with the physiological motion of the scanned object. By analyzing the received pilot tone signal, the motion signal of the scanned object can be obtained. Since the pilot tone device can be integrated into the local coil, the operation of the local coil, such as fixation and positioning, can be performed like a normal coil without additional operation. This is simple and easy for the operator to use, and it does not add burden to the scanned object as a sensor placed inside or on the skin.

[0025] When multiple signal channels are provided (e.g., multiple local coils), multi-channel signals can be obtained from multiple channels. However, typically, only high-quality single-channel signals that represent physiological movements (e.g., respiratory movements or heartbeats) are required.

[0026] According to embodiments of this disclosure, a method 100 for acquiring at least one target motion signal is proposed, see [link to relevant documentation]. Figure 1 Method 100 includes:

[0027] Step S110: Acquire multi-channel complex signals received from multiple channels, wherein each channel complex signal is a signal received after the high-frequency signal is modulated by at least one target motion signal of the scanned object during magnetic resonance scanning; and

[0028] Step S120: Using the motion signal synthesis vector corresponding to at least one target motion signal, obtain at least one target motion complex signal with interference removed from the multi-channel complex signal.

[0029] A multi-channel complex signal can be represented by a vector d(t), where d(t) is a 1×NT matrix, and N is a vector n. T The number of channels. In some embodiments, the signals received by the multiple channels are digitized data d(t), which can be directly received digitized data d(t) or digitized data d(t) obtained by analog-to-digital conversion of received analog data. The signals received by the multiple channels can be digitized data d(t) without preprocessing or digitized data d(t) after preprocessing.

[0030] In some embodiments, a high-frequency signal is transmitted via a transmitting antenna of a pilot tone device integrated in local coils. This high-frequency signal is, for example, a radio frequency signal outside the MRI band. During scanning of the object, the high-frequency signal transmitted by the pilot tone device is modulated by at least one target motion signal of the object and received by multiple local coils to obtain a pilot tone signal. In some examples, the pilot tone signal may be directly used as a multi-channel complex signal. In other examples, the multi-channel complex signal may be a pre-processed pilot tone signal, such as a pilot tone signal with a mean value of 0.

[0031] The target motion signal is, for example, a motion signal used for scanning navigation, such as a breathing signal or a heartbeat signal. Signals that cause distortion of the target motion signal, i.e., interference signals, can be external interference signals to the scanned object, such as radio frequency signals, or other unavoidable motion signals from the scanned object itself. The received multi-channel signal may contain desired signals and one or more unwanted signals. The desired signal is the target motion signal, such as a motion signal used for scanning navigation. Unwanted signals are interference signals. When scanning a human body, there are breathing and heartbeat movements. If the target motion signal is a breathing signal, then the heartbeat signal and MRI radio frequency signals are interference signals; if the target motion signal is a heartbeat signal, then the breathing signal and MRI radio frequency signals are interference signals.

[0032] In step S120, the motion signal synthesis vector corresponding to at least one target motion signal can maximize the target motion signal to be obtained as much as possible, while minimizing other signals that interfere with the target motion signal, such as radio frequency signals and other unavoidable motion signals of the scanned object.

[0033] See Figure 2 In step S120, the motion signal synthesis vector corresponding to at least one target motion signal is obtained in the following manner:

[0034] Step S210: Obtain data received by multiple channels within a set time period 0 to t2, wherein the data received by multiple channels within the set time period 0 to t2 includes data T1 without external interference within a first set sub-time period 0 to t1 and data T2 with external interference within a second set sub-time period t1 to t2;

[0035] Step S220: Based on the data T1 without external interference in the first set sub-period and the data T2 with external interference in the second set sub-period, obtain the external interference suppression matrix, and based on the data T1 without external interference or the data T2 with external interference and the external interference suppression matrix, obtain the data for suppressing external interference.

[0036] Step S230: Based on the data suppressing external interference and the frequency of at least one target motion signal, obtain the motion signal correlation matrix of at least one target motion signal in the frequency domain; and

[0037] Step S240: The eigenvector obtained based on the eigenvalues ​​of the motion signal correlation matrix is ​​used as the motion signal synthesis vector.

[0038] Using the above method, a high-quality single-channel complex signal representing the motion of at least one target can be obtained from a multi-channel complex signal. Preferably, the eigenvector corresponding to the largest eigenvalue of the motion signal correlation matrix is ​​taken as the motion signal synthesis vector.

[0039] In step S220, see Figure 3 The external interference suppression matrix can be obtained in the following ways.

[0040] Step S310: For the target motion signal, acquire data received by multiple channels within a set time period 0 to t2. The data T received by multiple channels within the set time period 0 to t2 includes data T1 without external interference within the first set sub-time period 0 to t1 and data T2 with external interference within the second set sub-time period t1 to t2. T1 and T2 serve as training data for the two stages.

[0041] As mentioned above, the signal that causes motion signal distortion, i.e., the interference signal, can be the MRI radio frequency (RF) signal. Pilot tone signals can be distorted by the MRI RF pulses used for imaging. This is because when an MRI RF pulse is applied, the local coil is exposed to a strong RF field, and the high RF energy couples to the input of the low-noise amplifier (LNA) or low-noise converter (LNC). This high RF energy will raise the temperature of the electronic equipment, causing a change in gain in the receiving channel and affecting the phase and amplitude of the received pilot tone signal. Therefore, to obtain useful physiological motion signals, this RF interference needs to be eliminated. If the interference signal is an MRI RF signal, then interference-free data is RF-interference-free data, and data with interference is RF-interference-affected data; the external interference suppression matrix is ​​the RF interference suppression matrix. Accordingly, the data received by multiple channels within a set time period can be: interference-free data T1 within the first set sub-time period 0–t1 before the calibration pulse sequence runs, and interference-affected data T2 within the second set sub-time period t1–t2 during the pulse sequence runs, wherein the calibration pulse sequence is the same as or substantially the same as the RF pulse sequence used for MRI imaging.

[0042] In some embodiments, the data received by multiple channels within the set time period in step S310 can be relatively stable data. For example, the set time period can be a period in which the periodic variation of the target motion signal is small. For physiological movements, such as breathing and heartbeat, after a phase of motion, such as after exhalation or myocardial contraction, there is a relatively resting phase in which signal acquisition has a relatively long period and the periodic variation of physiological movement is expected to be small, thereby expecting better measurement results. Exemplarily, Figure 4 The diagram shows the pilot tone signal received from one channel during a pulse sequence. Before time t1, no correction pulse sequence was applied, and the acquired data is the interference-free data T1. t2 is a short time interval after t1, during which the target motion changes little. The data acquired between t1 and t2 is the interference-affected data T2.

[0043] Step S320: For data received by multiple channels within a set time period, the interference-free data of the second set sub-time period is estimated using the interference-free data of the first set sub-time period. The increment of the interference-affected data T2 of the second set sub-time period t1~t2 relative to the estimated interference-free data of the second set sub-time period is used as correction data R. That is, the interference-affected data of the second set sub-time period is subtracted from the interference-affected data of the second set sub-time period to obtain correction data R1. The correction data constitute a correction matrix.

[0044] In step S320, to obtain the correction data R1 (pure external interference data), the external interference-free data for the second set sub-period can be estimated using the external interference-free data for the first set sub-period. For example, the external interference-free data for the first set sub-period can be averaged, and the calculated average data can be used as the estimated external interference-free data for the second set sub-period. Figure 4 As shown by the dashed line; or perform polynomial curve fitting on the interference-free data of the first set sub-period, and obtain the estimated interference-free data of the second set sub-period based on the fitted curve.

[0045] If data is received within multiple set time periods, the correction data within these multiple set time periods are averaged to obtain an average correction data R, which forms the correction matrix.

[0046] Step S330: Perform eigenvalue and eigenvector decomposition on the correction matrix, and remove eigenvectors whose energy accounts for a greater than a set threshold in the total energy of all eigenvectors or the eigenvector with the highest energy, to generate an external interference suppression matrix.

[0047] In step S330, based on the correction data R, R is obtained by the following formula. HThe eigenvector matrix of ×R, where R H It is the complex conjugate transpose of R. The calibration data is decomposed into eigenvalues ​​and eigenvectors. Eigenvectors whose energy percentage in the total energy of all eigenvectors exceeds a set threshold, or the eigenvector with the highest energy, are removed, generating an external interference suppression matrix. For example, for the calibration data R, we can assume the eigenvalues ​​are in ascending order, N... T This represents the number of channels or columns of the corrected data R, taken from the first N eigenvectors. T-b The column is used as the external interference suppression matrix, where b is usually 1 or 2, meaning it suppresses the first or second component with the greatest external interference. In this way, based on data received from multiple channels within one or more set time periods, the external interference suppression matrix is ​​obtained using interference-free data T1 within the first set sub-time period 0 to t1 and interference-containing data T2 within the second set sub-time period t1 to t2.

[0048] In some embodiments, taking radio frequency interference as an example, for the feature vector matrix V rf Perform the corresponding processing according to the following formula to obtain the external interference suppression matrix.

[0049] M rf =V rf ×O×V rf -1 (1)

[0050] Among them, V rf -1 It is V rf The inverse matrix, O is the identity matrix I, after passing through the eigenvector matrix V rf A matrix is ​​formed by replacing one or more row or column elements with 0 for eigenvectors whose eigenvector energy accounts for a greater than a set threshold of the total energy of all eigenvectors. For example, suppose the eigenvector matrix V... rf If the energy of the eigenvector in the last column of the identity matrix reaches a set threshold, such as 90%, then we can first set O = I, and then set O to O(n,n) = 0. That is, assuming the eigenvalues ​​are arranged in ascending order, setting the last row and last column of the identity matrix to 0 will yield matrix O. Alternatively, it can be obtained by replacing one row or column element corresponding to the eigenvector with the highest energy with 0, then V rf After *O, it is equivalent to V rf Set the eigenvector with the highest energy in V to 0, thus completing the process of V. rf Removal of the eigenvector with the highest energy.

[0051] As described above, using the external interference suppression matrix M rfBased on the data segment without external interference in the first set sub-time period or the data with external interference in the second set sub-time period, the data for suppressing external interference is estimated.

[0052] T1 rf =T1×M rf (2)

[0053] Among them, M rf T1 is the external interference suppression matrix, and T1 is the data without external interference within the first set sub-time period 0 to t1.

[0054] When only T2 is available, the data for suppressing external interference can also be calculated using the following equation (3):

[0055] T1 rf =T2×M rf (3)

[0056] Among them, M rf T1 is the external interference suppression matrix, and T2 is the data without external interference within the second set sub-time period t1 to t2.

[0057] Data T1 for suppressing external interference rf The motion signal correlation matrix C can be calculated. In some embodiments, see [link to relevant documentation]. Figure 5 In step S230, at least one target motion signal correlation matrix can be calculated in the following manner.

[0058] Step S510: Based on the frequency range of at least one target motion signal and the number of data samples within a set time period, obtain the frequency correlation matrix W of the at least one target motion signal.

[0059] The frequency correlation matrix W is a J*K matrix, where K is the number of data samples within at least one defined time period, and J can be the number of rows selected based on empirical values. Each row of the frequency correlation matrix represents a complex exponential signal of frequency, i.e. Where N is the number of samples per second. The frequency of the rows can be linearly spaced from the lower limit to the upper limit of the target motion signal frequency. For example, for a heartbeat signal, the frequency range is typically 0.7–2 Hz, and for a respiratory signal, the frequency range is typically 0.1–0.6 Hz. If J = 6, then for respiratory motion, the frequency of the rows corresponds to [0.1 Hz, 0.2 Hz, 0.3 Hz, 0.4 Hz, 0.5 Hz, 0.6 Hz].

[0060] Step S520: Based on the frequency correlation matrix of at least one target motion signal and at least one set time period of data T1 for suppressing external interference. rf To obtain the signal strength of at least one target motion in the frequency domain.

[0061] Step S530: Calculate at least one target motion signal correlation matrix based on the signal intensity of at least one target motion in the frequency domain.

[0062] If multiple target motion signals exist, for example, at least one target motion signal includes a first target motion signal and a second target motion signal, see [reference needed]. Figure 6 The correlation matrix of the first target motion signal and the correlation matrix of the second target motion signal are obtained in the following ways.

[0063] Steps S610 to S630, corresponding to steps S510 to S530, obtain the first target motion signal correlation matrix;

[0064] Step S640: Decompose the first target motion signal correlation matrix into eigenvalues ​​and eigenvectors, and remove the eigenvectors whose energy proportion in the total energy of all eigenvectors is greater than a set threshold or the eigenvector with the largest energy, to generate the first target motion suppression matrix;

[0065] Step S650: Based on the data of suppressing external interference and the first target motion suppression matrix, obtain data of suppressing external interference and the first target motion interference; and

[0066] Step S660: Based on the frequency correlation matrix of the second target motion signal and the data of suppressing external interference and first target motion interference, the second target motion correlation matrix is ​​obtained, wherein the frequency correlation matrix of the second target motion signal is obtained in the manner corresponding to step S510.

[0067] Taking a human body scan as an example, both breathing and heartbeat movements are present. For breathing movements, the respiratory movement correlation matrix can be obtained using the following equations (4-1) and (4-2):

[0068] F r =W r ×T1 rf (4-1)

[0069] Among them, F r W represents the signal intensity of respiratory motion in the frequency domain. r T1 is the frequency correlation matrix of respiratory movements. rf Data designed to suppress external interference.

[0070] C r =F r H ×F r (4-2)

[0071] Among them, C r This is the respiratory motion correlation matrix.

[0072] Respiratory and heartbeat signals are mixed together, so the respiratory signal can be considered as interference with the heartbeat signal. Before calculating the heartbeat motion correlation matrix, the interference of the respiratory signal on the heartbeat signal can be removed. The respiratory correlation matrix is ​​decomposed into eigenvalues ​​and eigenvectors, and eigenvectors whose energy percentage in the total energy of all eigenvectors is greater than a set threshold, or those with the highest energy, are removed, generating a respiratory suppression matrix, which is a matrix that suppresses or corrects respiratory interference. Specifically, V r For the eigenvectors of the respiratory motion correlation matrix obtained above, set the eigenvalues ​​to ascending order, N rf For T1 rf The number of channels or the number of columns in the matrix, take V. r The first N rf-b The column is the respiratory inhibition matrix M r Typically, b is 1 or 2, meaning it suppresses the first or second component of the respiratory signal that is strongest.

[0073] For heartbeat motion, the correlation matrix can be obtained using the following equations (5-1) to (5-3):

[0074] T1 r =T1 rf ×M r (5-1)

[0075] Among them, M r For the respiratory inhibition matrix, T1 r This is data that suppresses both external interference and respiratory signal interference.

[0076] F c =W c ×T1 r (5-2)

[0077] Among them, F c W represents the signal strength of heartbeat in the frequency domain. c T1 is the frequency correlation matrix of heartbeat. rf Data designed to suppress external interference.

[0078] C c =F c H ×F c (5-3)

[0079] Among them, C c This is the heartbeat motion correlation matrix.

[0080] As described above, in step S240, the eigenvector corresponding to the largest eigenvalue of the motion signal correlation matrix is ​​taken as the motion signal synthesis vector. For respiratory and heartbeat signals, the respiratory signal synthesis vector vr The respiratory motion correlation matrix C r The eigenvector corresponding to the largest eigenvalue, and the synthesized heartbeat signal vector v c The heartbeat motion correlation matrix C c The eigenvector corresponding to the largest eigenvalue.

[0081] As described above, in step S120, at least one target motion complex signal, free of interference, is obtained from the multi-channel complex signal using the motion signal synthesis vector corresponding to at least one target motion signal. For respiratory motion, d(t)×v r To maximize the respiratory signal and minimize external interference (such as radio frequency interference); for cardiac motion, d(t)×v c This maximizes the heartbeat signal while minimizing external interference (such as radio frequency interference) and respiratory signal interference. In this way, single-channel respiratory motion complex signals can be obtained.

[0082] The inventors noted that complex signals are not suitable for every application. In many applications, such as display and triggering applications, real signals are required. Therefore, in some embodiments, method 100 further includes: directing the maximum variance direction of at least one target motion complex signal, for example via d(t)×v r The obtained respiratory motion complex signal or through d(t)×v c The maximum variance direction of the obtained complex heartbeat motion signal is rotated to the real axis of the signal, and the real part of at least one target motion complex signal after rotation is taken. Noise is minimized along the maximum variance direction of the signal, thus a high-quality real signal of at least one target motion can be obtained through the above rotation. The maximum variance direction is obtained by obtaining the principal components of the real and imaginary parts of at least one target motion complex signal.

[0083] See Figure 7A and 7B , Figure 7A This schematically illustrates a complex signal of target motion. Figure 7B This schematically illustrates the complex motion signal of the target object, rotated to the real axis of the signal along the direction of maximum variance. Figure 7B The real part of the rotated signal shown can be used to obtain the real signal of the target motion.

[0084] At least one target motion of the scanned object, such as breathing or heartbeat, is a changing motion. In some embodiments, if the at least one target motion includes a first target motion and a second target motion, the signs of the first target motion signal and the second target motion signal are obtained using reference data. For the first target motion signal, the reference data is data obtained within a first sub-time period without external interference, after removing interference from the second target motion signal, rotating it to the direction of maximum variance, and taking the real part. For the second target motion signal, the reference data is data obtained within the first sub-time period without external interference, after removing interference from the first target motion signal, rotating it to the direction of maximum variance, and taking the real part. For example, when the scanned object is a human body, the reference data for respiratory motion can be obtained using the following formula:

[0085] T1 r = real(T1×v) r ×v r (6)

[0086] Among them, T1 r ′ represents the reference data for respiratory movements, T1 represents the data without external interference within the first sub-set time period, and v r For respiratory signal synthesis, r r is the rotation factor.

[0087] Reference data for heart rate can be obtained using the following formula:

[0088] T1 c = real(T1×v) c ×r c (7)

[0089] Among them, T1 c ′ represents reference data for heart rate movement, T1 represents data without external interference within the first sub-set time period, and v c For heartbeat signal synthesis, r c is the rotation factor.

[0090] Here, the signs of respiration and heartbeat can be determined based on the expected shapes of the respiratory and cardiac motion signals. Both respiratory and cardiac signals exhibit two offsets in opposite directions: for respiration, inhalation and exhalation; for heartbeat, contraction and relaxation. Since one signal offset is typically shorter in time than the other, the signal histogram is biased in the direction of one of the signal offsets. This property can be used to determine the sign of the signal, making one offset positive, typically making inhalation and cardiac relaxation positive.

[0091] In some examples, the direction of the signal is determined by the distance between the maximum and minimum signal values ​​and the mean of the reference data. If the difference between the maximum signal value and the mean of the reference data is greater than the difference between the mean of the reference data and the minimum signal value, the sign is 1. Conversely, if the difference between the maximum signal value and the mean of the reference data is less than the difference between the mean of the reference data and the minimum signal value, the sign is -1.

[0092] For example, the direction of breathing (inhalation / exhalation) can be determined using the maximum and minimum values ​​of the respiratory signal and the respiratory motion reference data T1. r It is calculated by the distance from the average value.

[0093] For heartbeat signals, first, the heartbeat motion reference data T1 is... c The mean of the filtered signal is subtracted, then a narrow front and back bandpass is applied, and finally the filter's settling effect is removed by eliminating the beginning and end portions of the filtered signal. Different moments of the signal are evaluated; preferably, the sign of the third moment produces the heartbeat sign.

[0094] Alternatively, the sign of the target motion can also be obtained based on the geometry of the equipment, such as the relative positions of the pilot tone generator, the heart position, and the receiving coil.

[0095] After obtaining the symbol of at least one target motion, at least one total target motion vector can be calculated based on the target motion composite vector, rotation coefficients, and motion symbol.

[0096] For respiratory movements:

[0097] m r =v r ×r r ×s r (8)

[0098] Among them, v r r is the synthesized respiratory signal vector; r s is the rotation coefficient of the respiratory signal; r The symbol for respiratory movements, +1 or -1; m r This is the total vector of respiratory signal synthesis.

[0099] Regarding heartbeat movements:

[0100] m c =v c ×r c ×s c (9)

[0101] Among them, v c r is the synthesized vector of heartbeat signals; c The rotation coefficient of the heartbeat signal; s c The symbol for heartbeat, +1 or -1; mc This is the total vector synthesized from the heartbeat signal.

[0102] By multiplying the multi-channel complex signal with the total vector synthesized from at least one target motion and taking the real part, a single-channel real signal representing at least one target motion can be obtained, which can characterize the symbol of at least one target motion.

[0103] For respiratory movements:

[0104] p r (t)=real(d(t)×m r (10)

[0105] Where, p r (t) represents the synthesized respiratory signal.

[0106] Regarding heartbeat movements:

[0107] p c (t)=real(d(t)×m c (11)

[0108] Where, p c (t) represents the synthesized heartbeat signal.

[0109] In some embodiments, method 100 further includes: removing spikes from the multi-channel complex signal using a spike removal function. Spike removal can be used, for example, to eliminate short-duration signal offsets caused by detuning transitions in the receiving coil. This offset is largely independent of the applied radio frequency power; therefore, the spike removal function can be obtained by: transmitting calibration data, which is a series (e.g., 10) of individual weak radio frequencies played at large pulse intervals (e.g., 200 ms); averaging the signal after the detuning transition to suppress other signals therein, and subtracting the average signal value before the radio frequency pulses to obtain a spike removal function f(TaRF), where TaRF represents "Time after retune event," and the spike removal function f(TaRF) is a matrix containing a complex vector for each receiving channel; storing the spike removal function and making it available to the real-time processing module when needed.

[0110] In response to the real-time processing module receiving information about the radio frequency pulse to be executed, for the currently processed sample, the most recently executed radio frequency pulse is determined by comparing timestamps, and TaRF is determined from the timestamp difference between the re-modulation event of the radio frequency pulse and the timestamp of the currently processed sample; and in response to the request to remove spikes, f(TaRF) is subtracted from the current sample.

[0111] In embodiments of this disclosure, in order to improve the suppression of external interference (such as radio frequency interference), in addition to applying an external interference suppression matrix, the multi-channel complex signal can be spike-removing processed before multiplying the multi-channel complex signal with the composite vector of at least one target motion signal.

[0112] According to another aspect of this disclosure, an apparatus 800 for acquiring target physiological motion signals is proposed. The apparatus 800 includes: a first unit 810 configured to acquire a multi-channel complex signal received by multiple channels, each of the multi-channel complex signals being a signal received after a high-frequency signal in a magnetic resonance scan is modulated by at least one target motion signal of the scanned object; and a second unit 820 configured to obtain at least one target motion complex signal with interference removed from the multi-channel complex signal using a motion signal synthesis vector corresponding to at least one target motion signal. The second unit includes 820: a first subunit 821 configured to acquire data received by multiple channels within a set time period, wherein the data received by multiple channels within the set time period includes data without external interference within a first set sub-time period and data with external interference within a second set sub-time period; a second subunit 822 configured to obtain an external interference suppression matrix based on the data without external interference within the first set sub-time period and the data with external interference within the second set sub-time period, and to obtain data with suppressed external interference based on the data without external interference or the data with external interference and the external interference suppression matrix; a third subunit 823 configured to obtain a motion signal correlation matrix of at least one target motion signal in the frequency domain based on the data with suppressed external interference and the frequency of at least one target motion signal; and a fourth subunit 824 configured to use the eigenvector obtained from the eigenvalues ​​of the motion signal correlation matrix as the motion signal synthesis vector.

[0113] According to another aspect of this disclosure, an electronic device is proposed, including at least one processor and a memory communicatively connected to the at least one processor, wherein the memory stores a computer program that, when executed by the at least one processor, implements the method described above according to any of the above embodiments.

[0114] According to another aspect of this disclosure, a pilot tone device is proposed, comprising: a transmitter for transmitting a high-frequency signal, the high-frequency signal being a radio frequency signal outside the frequency band of a magnetic resonance radio frequency signal; a multi-channel receiver for receiving a high-frequency signal modulated by a first physiological motion signal and a second physiological motion signal of a scanned object during a magnetic resonance scan; and the aforementioned electronic device.

[0115] According to another aspect of this disclosure, a magnetic resonance imaging (MRI) device is proposed, including the pilot tone device of any of the above embodiments. The pilot device has a transmitting antenna that can be integrated into a local coil placed on the scanned object. Operation of the local coil, such as fixing and positioning, can be performed like that of a normal coil without additional operation, which is simple and easy for the operator to perform, and also does not add burden to the scanned object due to sensors placed internally or on the skin.

[0116] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing a computer program is provided, wherein the computer program implements the method according to any of the above embodiments when executed by a processor.

[0117] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, wherein the computer program, when executed by a processor, implements the method according to any of the above embodiments.

[0118] Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0119] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0120] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0121] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0122] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0123] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0124] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0125] While embodiments or examples of this disclosure have been described with reference to the accompanying drawings, it should be understood that the methods, systems, and devices described above are merely exemplary embodiments or examples, and the scope of the invention is not limited by these embodiments or examples, but only by the granted claims and their equivalents. Various elements in the embodiments or examples may be omitted or replaced by their equivalents. Furthermore, the steps may be performed in a different order than that described in this disclosure. Further, various elements in the embodiments or examples may be combined in various ways. Importantly, as the technology evolves, many elements described herein can be replaced by equivalents that appear after this disclosure.

[0126] The above description is merely an embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for acquiring at least one target motion signal, comprising: Acquire multi-channel complex signals received from multiple channels, wherein each channel complex signal is a signal received after a high-frequency signal is modulated by at least one target motion signal of the scanned object during magnetic resonance scanning; Using the motion signal synthesis vector corresponding to at least one target motion signal, at least one interference-free target motion complex signal is obtained from the multi-channel complex signal, wherein the motion signal synthesis vector corresponding to at least one target motion signal is obtained in the following manner: Acquire data received by multiple channels within a set time period, wherein the data received by multiple channels within the set time period includes data without external interference within a first set sub-time period and data with external interference within a second set sub-time period; Based on the data without external interference in the first set sub-period and the data with external interference in the second set sub-period, an external interference suppression matrix is ​​obtained, and based on the data without external interference or the data with external interference and the external interference suppression matrix, data for suppressing external interference is obtained. Based on the frequency range of at least one target motion signal and the number of data samples within a set time period, a frequency correlation matrix of the at least one target motion signal is obtained; Based on the frequency correlation matrix of the at least one target motion signal and the data of suppressing external interference within at least one set time period, a motion signal correlation matrix of at least one target motion signal in the frequency domain is obtained. The eigenvector obtained from the eigenvalues ​​of the motion signal correlation matrix is ​​used as the motion signal synthesis vector.

2. The method according to claim 1, wherein, The largest eigenvector corresponding to the largest eigenvalue of the motion signal correlation matrix is ​​taken as the motion signal synthesis vector.

3. The method according to claim 1, wherein, Rotate the direction of maximum variance of the at least one target motion complex signal to the real axis of the signal and take its real part.

4. The method according to claim 1, wherein, The external interference suppression matrix is ​​obtained in the following way: The interference-free data for a second predetermined sub-period is predicted using the interference-free data for a first predetermined sub-period. The increment of the interference-affected data for the second predetermined sub-period relative to the predicted interference-free data for the second predetermined sub-period is used as correction data, and this correction data forms a correction matrix. The correction matrix is ​​decomposed into eigenvalues ​​and eigenvectors, and eigenvectors whose energy accounts for a greater than a set threshold of the total energy of all eigenvectors or eigenvectors with the highest energy are removed to generate an external interference suppression matrix.

5. The method according to claim 4, wherein, Acquire data received from multiple channels within multiple set time periods. The data within each set time period includes data without external interference in the first set sub-time period and data with external interference in the second set sub-time period. Obtain the calibration data for each set time period; and The average value of multiple correction data is calculated to obtain average correction data, which constitutes the correction matrix.

6. The method according to claim 4 or 5, wherein, The data without external interference is data without radio frequency interference, the data with external interference is data with radio frequency interference, and the external interference suppression matrix is ​​a radio frequency interference suppression matrix.

7. The method according to claim 1, wherein, The at least one target motion signal includes a first target motion signal and a second target motion signal, wherein the first target motion signal is one of a heartbeat signal and a respiration signal, and the second target motion signal is the other of a heartbeat signal and a respiration signal. Obtain the correlation matrix of the motion signal of the first target; The correlation matrix of the first target motion signal is decomposed into eigenvalues ​​and eigenvectors, and the eigenvectors whose energy proportion in the total energy of all eigenvectors is greater than a set threshold or whose energy is the largest are removed to generate the first target motion suppression matrix. Based on the data for suppressing external interference and the first target motion suppression matrix, data for suppressing external interference and the first target motion interference are obtained; and The second target motion correlation matrix is ​​obtained based on the frequency correlation matrix of the second target motion signal and the data of suppressing external interference and first target motion interference.

8. The method according to claim 1, wherein, The at least one target motion signal includes a first target motion signal and a second target motion signal, and the method further includes: The symbols of the first target motion signal and the second target motion signal are obtained using reference data. For the first target motion signal, the reference data is the data obtained in the first sub-time period without external interference, after removing the interference of the second target motion signal, rotating it to the direction of maximum variance, and taking the real part. For the second target motion signal, the reference data is the data obtained in the first sub-time period without external interference, after removing the interference of the first target motion signal, rotating it to the direction of maximum variance, and taking the real part.

9. The method according to claim 1, further comprising: The multi-channel complex signal is processed to remove spikes using a spike removal function.

10. An apparatus for acquiring at least one target motion signal, the apparatus comprising: The first unit is configured to acquire multi-channel complex signals received through multiple channels, wherein each channel complex signal is a signal received after a high-frequency signal is modulated by at least one target motion signal of the scanned object during magnetic resonance scanning. The second unit is configured to obtain at least one target motion complex signal after interference removal from the multi-channel complex signal using a motion signal synthesis vector corresponding to at least one target motion signal. The second unit includes: The first subunit is configured to acquire data received by multiple channels within a set time period, wherein the data received by multiple channels within the set time period includes data without external interference within a first set sub-time period and data with external interference within a second set sub-time period. The second subunit is configured to obtain an external interference suppression matrix based on the data without external interference in the first set sub-period of each of the at least one time period and the data with external interference in the second set sub-period, and to obtain data that suppresses external interference based on the data without external interference or the data with external interference and the external interference suppression matrix. The third subunit is configured to obtain the frequency correlation matrix of the at least one target motion signal based on the frequency range of the at least one target motion signal and the number of data samples within a set time period. Based on the frequency correlation matrix of the at least one target motion signal and data suppressing external interference within at least one set time period, obtain the motion signal correlation matrix of the at least one target motion signal in the frequency domain; and The fourth subunit is configured to use the eigenvector obtained from the eigenvalues ​​of the motion signal correlation matrix as the motion signal synthesis vector.

11. A pilot tone device, comprising: The transmitter is used to transmit high-frequency signals, which are radio frequency signals outside the frequency band of magnetic resonance radio frequency signals; A multi-channel receiver is used to receive high-frequency signals modulated by the first and second target motion signals of the scanned object during magnetic resonance scanning. as well as An electronic device, the electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program that, when executed by the at least one processor, implements the method according to any one of claims 1-9.

12. A non-transitory computer-readable storage medium storing a computer program, wherein, The computer program, when executed by a processor, implements the method according to any one of claims 1-9.

13. A computer program product comprising a computer program, wherein, The computer program, when executed by a processor, implements the method according to any one of claims 1-9.

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